code: def test_validate_estimator_init():
      smote = SMOTE(random_state=RND_SEED)
      tomek = TomekLinks(sampling_strategy="all")
      smt = SMOTETomek(smote=smote, tomek=tomek, random_state=RND_SEED)
      X_resampled, y_resampled = smt.fit_resample(X, Y)
      X_gt = np.array(
          [
              [0.68481731, 0.51935141],
              [1.34192108, -0.13367336],
              [0.62366841, -0.21312976],
              [1.61091956, -0.40283504],
              [-0.37162401, -2.19400981],
              [0.74680821, 1.63827342],
              [0.61472253, -0.82309052],
              [0.19893132, -0.47761769],
              [1.40301027, -0.83648734],
              [-1.20515198, -1.02689695],
              [-0.23374509, 0.18370049],
              [-0.00288378, 0.84259929],
              [1.79580611, -0.02219234],
              [0.38307743, -0.05670439],
              [0.70319159, -0.02571667],
              [0.75052536, -0.19246518],
          ]
      )
      y_gt = np.array([1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0])
      assert_allclose(X_resampled, X_gt, rtol=R_TOL)
      assert_array_equal(y_resampled, y_gt)
  
file_path: imbalanced-learn/imblearn/combine/tests/test_smote_tomek.py
imports: import numpy
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from imblearn.combine import SMOTETomek
  from imblearn.over_sampling import SMOTE
  from imblearn.under_sampling import TomekLinks
label_desc: Use image node_id 3 for calling a global function with example usage: test_validate_estimator_init() without return types